Improvements to InfluxDB include improved ingest performance, unlimited data cardinality, and exceptionally low latency querying.
InfluxData is releasing an updated version of the databases it markets under the name InfluxDB 3.0, it said Wednesday.
The updates to InfluxDB 3.0 are aimed at easing development of applications based on time-series data, and include improved Ingest performance, real-time querying, and superior data compression through native object storage to power high-cardinality.
The new features are now generally available, and will support observability, real-time analytics, and IoT/IIoT, the company said, adding that the improvements have been added in order to support the demand of complex, sophisticated workloads that have proliferated due to the evolution of AI systems.
The company’s InfluxDB Cloud Dedicated and InfluxDB Clustered products have also been updated.
InfluxDB Cloud Dedicated, the company’s fully managed time series database-as-a-service (DBaaS) for enterprise-grade workloads, received enhancements including a new operational dashboard that will provide visual insights into the performance and health of dedicated clusters, enabling developers to detect unintended workload changes, identify potential bottlenecks, and optimize cluster performance.
Other updates to the database-as-a-service offering include single sign-on (SSO) integration enabling enterprise developers to seamlessly access clusters using existing credentials and streamlining the login process, the company said. New APIs for management and token management are also present, enabling enterprises to automate administrative tasks such as managing users, databases, and tokens within their InfluxDB Cloud Dedicated cluster, it said.
These enhancements, according to David Menninger, executive director of software research at advisory firm ISG, enable enterprises with security or performance concerns to have their own dedicated set of resources.
“Since the infrastructure is not shared, there are less concerns about contention for resources that may affect performance and less opportunities for access to potentially sensitive data,” Menninger said.
InfluxDB Clustered, released last year, has also received the same performance and storage updates to help enterprises lower cost but boost efficiency, the company said.
The clustered version, Menninger said, is useful to enterprises wanting to access InfluxDB’s latest features in an on-premises configuration.
He expects the upgrades made to the core engine of InfluxDB to make it more competitive against rivals such as QuestDB and TimescaleDB.
InfluxDB 3.0 was rewritten around a stack of Apache open-source projects including Arrow, Data Fusion, Flight SQL and Parquet.
While Arrow provides an in-memory columnar format, Data Fusion, Flight SQL, and Parquet provide a query engine with SQL processing capabilities, a protocol for SQL interactions with databases, and an open columnar oriented data storage format that is widely used by data platforms, respectively, Menninger explained.
“InfluxDB is designed to support the most demanding real-time, time series workloads requiring high throughput and low latency. They claim to be able to ingest millions of data values per second,” he said.
Some of the database’s use cases include security event monitoring and network monitoring to determine if systems are operating properly and at peak efficiency.
